Estimation of signal distortion using effective sampling density for light field-based free viewpoint video

In a light field-based free viewpoint video (LF-based FVV) system, effective sampling density (ESD) is defined as the number of rays per unit area of the scene that has been acquired and is selected in the rendering process for reconstructing an unknown ray. This paper extends the concept of ESD and shows that ESD is a tractable metric that quantifies the joint impact of the imperfections of LF acquisition and rendering. By deriving and analyzing ESD for the commonly used LF acquisition and rendering methods, it is shown that ESD is an effective indicator determined by system parameters and can be used to directly estimate output video distortion without access to the ground truth. This claim is verified by extensive numerical simulations and comparison to PSNR. Furthermore, an empirical relationship between the output distortion (in PSNR) and the calculated ESD is established to allow direct assessment of the overall video distortion without an actual implementation of the system. A small scale subjective user study is also conducted which indicates a correlation of 0.91 between ESD and perceived quality

On the outage of multihop parallel relay networks

In this paper we analyze the outage probability of a cooperative multihop parallel relay network in Nakagami-m fading channels. The general closed form expression of the outage probability is derived both for integer and arbitrary Nakagami parameter m. We present numerical results on the performance of the network. It shows a careful configuration of the network size and power sharing between nodes can ensure optimal outage performance in the network

Engaging Students with Flipped Classes Using 3D Video Collaboration Technology

The objective of this paper is to demonstrate the potential of 3D video collaboration technologies to engage students with the learning materials prior flipped classes. The study uses iSee designed for 3D video collaborative classes and compared it with online learning management systems. An experiment has been reported on 273 students in an undergraduate Information System course. It was revealed that the correlation between either the students’ engagement on the online quizzes or their engagement on iSee discussions with their learning outcomes were high. However, our statistical analysis showed that the relationship between iSee engagement and students’ learning outcomes was stronger. The qualitative observations during this experiment are also discussed. The results have been discussed in the lens of Theory of Peer Learning and the future research have been suggested. This study motivates teaching practitioners in Information Systems to use 3D video collaboration technologies in flipped classes

Autocorrelation Based Transmission Power Control in WBANs

In this paper, we propose an autocorrelation-based transmission power control (A-TPC) method to increase the transmission reliability and reduce the energy consumption. In A-TPC, data packets from multiple sensor nodes are scheduled in the TDMA-fashion. The transmission power level and the slot scheduling are jointly optimized based on a temporal autocorrelation model. The channel datasets collected from real WBAN daily scenarios are imported into our simulation model to evaluate the performance of A-TPC. Simulation results demonstrate that A-TPC significantly improves the transmission reliability and reduces the energy consumption

A Real-Time Facial Expression Recognition System for Online Games

Multiplayer online games (MOGs) have become increasingly popular because of the opportunity they provide for collaboration, communication, and interaction. However, compared with ordinary human communication, MOG still has several limitations, especially in communication using facial expressions. Although detailed facial animation has already been achieved in a number of MOGs, players have to use text commands to control the expressions of avatars. In this paper, we propose an automatic expression recognition system that can be integrated into an MOG to control the facial expressions of avatars. To meet the specific requirements of such a system, a number of algorithms are studied, improved, and extended. In particular, Viola and Jones face-detection method is extended to detect small-scale key facial components; and fixed facial landmarks are used to reduce the computational load with little performance degradation in the recognition accuracy

Combined adaptive lattice reduction-aided detection and antenna shuffling for DSTTD-OFDM systems

In this paper, we consider lattice reduction (LR) aided linear detection in a DSTTD-OFDM (double space-time transmit diversity- orthogonal frequency division multiplexing) system with antenna shuffling. We first derive an antenna shuffling criterion for the LR-aided DSTTD-OFDM system. Next, we propose a combined reduced-feedback and adaptive LR algorithm by exploiting the correlation between OFDM subcarriers in the frequency domain. The LR-aided DSTTD OFDM system with this algorithm requires low computational effort for the LR operation and small feedback information. Simulation results show that a significant improvement could be achieved in the proposed system compared to previous (non-LR-aided) systems under spatially correlated channels. Also, the proposed complexity-reduced approach could greatly lower the system complexity while exhibiting a slight performance loss

A real-time facial expression recognition system for online games

Multiplayer online games (MOGs) have become increasingly popular because of the opportunity they provide for collaboration, communication, and interaction. However, compared with ordinary human communication, MOG still has several limitations, especially in communication using facial expressions. Although detailed facial animation has already been achieved in a number of MOGs, players have to use text commands to control the expressions of avatars. In this paper, we propose an automatic expression recognition system that can be integrated into an MOG to control the facial expressions of avatars. To meet the specific requirements of such a system, a number of algorithms are studied, improved, and extended. In particular, Viola and Jones face-detection method is extended to detect small-scale key facial components; and fixed facial landmarks are used to reduce the computational load with little performance degradation in the recognition accuracy

Characterising the interactions between unicast and broadcast in IEEE 802.11 ad hoc networks

This paper investigates the relative performance of unicast and broadcast traffic traversing a one-hop ad hoc network utilising the 802.11 DCF. An extended Markov model has been developed and validated through computer simulation, which successfully predicts the respective performance of unicast and broadcast in a variety of mixed traffic scenarios. Under heavy network traffic conditions, a significant divergence is seen to develop between the performance of the two traffic classes - in particular, when network becomes saturated, unicast traffic is effectively given higher precedence over broadcast. As a result, the network becomes dominated by unicast frames, leading to poor rates of broadcast frame delivery